ADD method for meta-analysis
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\newacronym{moi}{MOI}{multiplicity of infection}
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\newacronym{ifng}{IFN$\upgamma$}{interferon-$\upgamma$}
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\newacronym{tnfa}{TNF$\upalpha$}{tumor necrosis factor-$\upalpha$}
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\newacronym{sql}{SQL}{structured query language}
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\newacronym{fcs}{FCS}{flow cytometry standard}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% SI units for uber nerds
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@ -1056,6 +1058,34 @@ via a Biorad Bioplex 200 plate reader.
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\input{../tables/luminex_panel.tex}
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\end{table}
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\subsection{data aggregation and meta-analysis}
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In order to perform meta-analysis on all experimental data generate using the
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\gls{dms} system, we developed a program to curate and aggregate the raw
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datafiles into a \gls{sql} database.
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% FIGURE summarize this stuff in a picture
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The data files to be aggregated included Microsoft Excel files which held
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timeseries measurements for cell cultures (eg cell counts, viability, glucose,
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\gls{il2} added, media added, and media removed), \gls{fcs} files for cellular
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phenotypes, and FlowJo files which held gating parameters and statistics based
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on the \gls{fcs} files. Additional information which was held in electronic lab
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notebooks (eg OneNote files) was not easily parsable, and thus this data was
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summarized in YAML files. The data included in these YAML files included reagent
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characteristics (vendor, catalog number, lot number, manufacturing date), cell
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donor characteristics (age, \gls{bmi}, phenotype, demographic, gender), and all
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experimental parameters such as the number of bead or \gls{dms} added.
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% FIGURE data model
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To aggregate the data in a database, we wrote a program using Python, R, and
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Docker which retrieved the data from its source location and inserted the data
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in a Postgres database. This program included checks to ensure the integrity of
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source data (for example, flagging entries which had a reagent whose
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manufacturing date was after the date the experiment started, which signifies a
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human input error).
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\subsection{statistical analysis}
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For 1-way \gls{anova} analysis with Tukey multiple comparisons test,
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context of pure error). Statistical significance was evaluated at $\upalpha$ =
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0.05.
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% METHOD add meta-analysis
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% METHOD add Grex
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\section{results}
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\subsection{DMSs can be fabricated in a controlled manner}
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